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A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions
Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purpose...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842776/ https://www.ncbi.nlm.nih.gov/pubmed/24288140 http://dx.doi.org/10.1093/database/bat080 |
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author | Davis, Allan Peter Wiegers, Thomas C. Roberts, Phoebe M. King, Benjamin L. Lay, Jean M. Lennon-Hopkins, Kelley Sciaky, Daniela Johnson, Robin Keating, Heather Greene, Nigel Hernandez, Robert McConnell, Kevin J. Enayetallah, Ahmed E. Mattingly, Carolyn J. |
author_facet | Davis, Allan Peter Wiegers, Thomas C. Roberts, Phoebe M. King, Benjamin L. Lay, Jean M. Lennon-Hopkins, Kelley Sciaky, Daniela Johnson, Robin Keating, Heather Greene, Nigel Hernandez, Robert McConnell, Kevin J. Enayetallah, Ahmed E. Mattingly, Carolyn J. |
author_sort | Davis, Allan Peter |
collection | PubMed |
description | Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88 629 articles relating over 1 200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 2 54 173 toxicogenomic interactions (1 52 173 chemical–disease, 58 572 chemical–gene, 5 345 gene–disease and 38 083 phenotype interactions). All chemical–gene–disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer’s text-mining process to collate the articles, and CTD’s curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug–disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades’ worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/ |
format | Online Article Text |
id | pubmed-3842776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-38427762013-12-02 A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions Davis, Allan Peter Wiegers, Thomas C. Roberts, Phoebe M. King, Benjamin L. Lay, Jean M. Lennon-Hopkins, Kelley Sciaky, Daniela Johnson, Robin Keating, Heather Greene, Nigel Hernandez, Robert McConnell, Kevin J. Enayetallah, Ahmed E. Mattingly, Carolyn J. Database (Oxford) Original Article Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88 629 articles relating over 1 200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 2 54 173 toxicogenomic interactions (1 52 173 chemical–disease, 58 572 chemical–gene, 5 345 gene–disease and 38 083 phenotype interactions). All chemical–gene–disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer’s text-mining process to collate the articles, and CTD’s curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug–disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades’ worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/ Oxford University Press 2013-11-28 /pmc/articles/PMC3842776/ /pubmed/24288140 http://dx.doi.org/10.1093/database/bat080 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Davis, Allan Peter Wiegers, Thomas C. Roberts, Phoebe M. King, Benjamin L. Lay, Jean M. Lennon-Hopkins, Kelley Sciaky, Daniela Johnson, Robin Keating, Heather Greene, Nigel Hernandez, Robert McConnell, Kevin J. Enayetallah, Ahmed E. Mattingly, Carolyn J. A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title | A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title_full | A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title_fullStr | A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title_full_unstemmed | A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title_short | A CTD–Pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
title_sort | ctd–pfizer collaboration: manual curation of 88 000 scientific articles text mined for drug–disease and drug–phenotype interactions |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842776/ https://www.ncbi.nlm.nih.gov/pubmed/24288140 http://dx.doi.org/10.1093/database/bat080 |
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